Estimation of structure-function relations in neuropsychology is frequently problematic as the used data do not meet distributional assumptions of the statistics used to estimate these relations. Robust statistics aid researchers in producing stable and reliable estimators when the data are not-normal and include outliers. The study examined robust properties of five correlational estimates in 54 children with spina bifida. Using a bootstrap sampling process, the Pearson correlation was compared with four robust correlations: the percentage bend correlation, the Winsorized correlation, the skipped correlation using the Donoho-Gasko median, and the skipped correlation using the minimum volume ellipsoid estimator. Across methods, results yielded similar estimates of the structure-function relations, suggesting the lack of these relations is not easily attributed to violations of distributional assumptions. Simultaneous use of the Pearson correlation along with robust correlations strengthened inferences. The bootstrap process involving multiple passes on the same data further strengthened conclusions by providing more reliable estimates of standard errors.